Introduction

My primary motivation was to explore reviews of different types of movies posted by users located in different regions based on the data source from Twitter. So I chose five recent movies, Murder on the Orient Express, Coco, Justice League, Daddy’s Home 2, Wonder, as my research subjects.

The analysis will help the moviegoers and the movie industry improve box-office results and help people easily decide what kind of movies to see basis their interests.

Number of Tweets

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Change of Number of Tweets over Time

Top Tweeters

Top Tweeters

Top Tweeters

Top Tweeters

Top Tweeters

Platforms of Users

Density of Original Tweets and Retweets

Retweet Network

Retweet Network of Orient Express

Retweet Network of Coco

Retweet Network of Justice League

Retweet Network of Daddy’s Home 2

Retweet Network of Wonder

World Map

USA Map

States Map

States Map

States Map

States Map

States Map

Trending Words

Most Common Words about Orient Express

Most Common Words about Coco

Most Common Words about Justice League

Most Common Words about Daddy’s Home 2

Most Common Words about Wonder

Sentiment Over Time about Orient Express

Sentiment Over Time about Coco

Sentiment Over Time about Justice League

Sentiment Over Time about Daddy’s Home 2

Sentiment Over Time about Wonder

Emoji Reactions to Orient Express

Emoji Reactions to Coco

Emoji Reactions to Justice League

Emoji Reactions to Daddy’s Home 2

Emoji Reactions to Wonder

Conclusion

With the use of plethora of features in R, the analysis will provide key insights about those five movies, including timeline of tweets, user platforms of tweets, retweet network, etc. Also, maps were made to locate the tweets. The data was then reviewed graphically to explore the trending words in twitter about those movies and sentiment analysis was done using word cloud, line plots and horizontal bar charts, to tell us that how different customers react to different types of movies.

Various results and analysis showed that most people in USA prefer action movies, then animation movie, like Coco. The comedy Daddy’s Home 2 is least noticed in twitter. Besides, based on the states maps, people in California, Texas, Florida, New York and Virginia tweets more about those movies. But sentiment analysis, and emoji analysis, all together show us positive reactions of customers associated with the movies. win, love, prize, and Perfect - customers associate movie with positive words like these. This can help movie industry in understanding how branding and associating with these words can further help them improving box office.